The work aims to use multi-population genetic algorithm (MPGA) to optimize the parameters to solve the difficulty in setting parameters in the control of the traditional PID hydraulic jacking system for packaging and transportation. The multi-population genetic algorithm was used to combine the algorithm with conventional PID control. The hydraulic system was analyzed. A mathematical model of the hydraulic system was established and applied to the controlled object of the PID control strategy after the algorithm optimization. The effectiveness of multi-population genetic algorithm for PID control strategy optimization was investigated by comparing with the optimized parameters of general genetic algorithm. The simulation result showed that, parameters optimized by the multi-population genetic algorithm can make the controlled object converge to steady state quickly. The whole system had fast response speed, small steady-state error and small overshoot. However, the parameters obtained by general genetic algorithm fell into local optimum and cannot get global optimum solution in a short time. The proposed optimization algorithm has a good effect on PID parameter setting and can meet the control requirements of the system.